[MUSIC] Welcome back, here we are transitioning from discussing story considerations to going back to demonstrating how to incorporate these into telling your data story using Tableau. This is the first in a series of three related screen cast lessons that will build up to telling a data story using our super story data set. Each of these screen casts will build directly on the one preceding it. Therefore I highly recommend you watch them in order, and I believe your learning will be enhanced, if you can watch them in one sitting. We are setting out to tell the story of those customers who appear to have a lot of sales, yet the profit is a loss. Notice that I'm making it ambiguous on purpose, because that's the type of question we're going to get. Sometimes we'll get the specificity we need, those are the easy ones. Most of the time, however, we'll get some ambiguity. When starting with that ambiguity, it means we want to delve into the data and provide a very specific, very tight story about the data. When the story is complete, we will have, more or less, specificity. So follow along as I demonstrate how to start with an ambiguous question. And turn it into a story that serves the needs of stakeholders and the audience, so let's get started. This is first of several lessons in developing a story. And so what we're going to do here is we are going to look at a previous dashboard that we did. And we're going to take the question that we had before, which is customers who have a quote, unquote a lot of sales, but profit is negative. In other words, they have a loss even though there's a lot of revenue. And so what we're going to do is we're going to put up a comparison. And we're going to just see how it looks and sort of explain why it might be that there are customers who are drawing losses, even though they buy a lot of stuff. And so what we're going to do is we're just going to start with the dashboard that we've created before. And as you can see, I'm just going through to sort of look at some of the stuff. And you can see here we have Sean Miller, Becky Martin and down further is Graham Thornton. And then there's two people who seem to have a lot of profit and a lot of sales, Tamara Chand and Raymond Buch. So we're going to have those people in our little mix as we setup the visualization. So, as you could see, is what we're going to do now is we're going to go and we're going to actually Duplicate this particular worksheet. We're going to go to customer rank first, so you just click over there. We've created this before, and then we'll just right click on this and then we'll click Duplicate. And the reason is that I like the format, so I'm just going to keep the format as is. It's called sheet 7, I'll just keep it as sheet 7. And you can see, it's exactly the same thing, of course. It is Duplicated, nothing fancy there. And so what I'm going to do now, is I'm going to do something here. I'm going to select more than one, Of these people. So Sean Miller and Tamara Chand, Raymond Buch, Becky Martin and then down at the very bottom you can see Graham Thornton. So the way you're going to select it is, you're going to select it by holding down the Ctrl button while you're clicking each one. So that you can select them multiple ways. So, you select those five, and then you hover over one of them, and when you hover over one of them, you can say Keep Only. So, I'm going to just Keep Only, there. Click on that, and then those five are going to be there. So, those are the ones that we're going to be studying. So we have all the customers, but we're going to concentrate on five of them. Three of them have losses despite having a lot of sales. Two of them have profits in addition to having a lot of sales. And so now I'm going to drag profit, sum of profit over to the columns. And I'm going to remove the sum of sales, because what I really want to see is profit. And now we can see exactly what's going on here. That Tamara Chand, Raymond Busch have nice profits. Sean Miller, Becky Martin and Graham Thornton do not. So let's go ahead and I'm going to do a bit of fiddling with this. As you can see here, I'm moving the customer name up, mainly because I want to be able to do further analysis, and I know what's coming. So I'm moving the customer name up to columns to get a sense of this. I'm also going to do a Sort here, I'm going to press Sort. And I'm going to do a custom Sort, I'm going to do a manual drag. There's only five names, I'm going to just drag them. And here I'm just clicking on Manual, so that I can, get all of the people who made, or who had loses together, and those that had profits together. So Shawn Miller, Becky Martin and Graham Thornton are going to be up. Tamara Chan and Raymond Busch are going to be below. So that we have the people who made losses first, people who have gains second. And so we can see here those that had losses are first. Those that have profits are second, so there you go. That's that for this particular Visualization. I'm going to Duplicate this again, so I'm going to right click, click on Duplicate. It'll pop up sheet eight or however many sheets you have, and now I'm going to drag away the customer profit and add discount. And it's automatically going to do average discount, which is totally cool. And the reason is that I want to be able to look at the discount and see if there's a difference between those that made a loss, or gave us a loss. And those that gave us a profit. Were they given bigger discounts, were the discounts too big? Which means it sent those customers into loss making for us. Whereas those that made profits didn't have as much of a discount. So that's part of the interest there. And so, you can see that, that's very clear, actually, that the three who made losses. So now the next step in our exercise is that we are going to add a category to this. And we're going to put the particular field up and then we're going to put the category and we're going to put it in rows. And so, we can see now that there is an interesting dynamic where technology appears to be either very profitable or very not profitable depending on the customer. Which is already an interesting piece of information. Furniture and office supplies, not so much. And so you can even expand this, you could do subcategory and see that. And so now what I'm going to do, you can just see that, right there, just showing you here. And now what I'm going to do is Duplicate. Actually I think I skipped a step there, but what I did was create discounts. And I want to Duplicate this again, and then I'm going to create another visualization that highlights it. But as you can see, discounts are pretty stark right? The big discounts to those who made losses, not very big discounts to those who didn't. So when we go to, let's Duplicate one more time here. All right, now, and then what I'm going to do is I'm going to drag away discount. And now I'm going to add state, and so this is interesting because the obvious way to do this could be to do a map. You can do a state, you could put each state on a map, and then you could see the pattern. But I'm not going to do that, it's actually probably easier to do it that way, but I'm not going to because it doesn't get at the story. And that's a key point is that the state on a map may look nice and it may be easier. But oftentimes is not as effective in conveying the information. And now, all I'm doing here is just dragging the state field to the rows shelf. Drag this state field to the rows shelf, and then you'll get the rows in a nice spot. Yeah, I'm just doing some minor formatting here, nothing fancy. Your mileage may vary on the amount of formatting, but you can see here that we can look at the states involved with the customer. If you look at Texas, wow, that's pretty big, pretty big loss there for that one. And then, so interestingly, like I said, you can expand it down. In fact, you can take out the product name, because it may be too fine grained. And then you can see, actually, by manufacturer, this is interesting, right? By manufacturer, there's no interesting things go on right with binders even and things like that, that may be of interest to people.
